CHLOROPHYLL ESTIMATION OF LAKE WATER AND COASTAL WATER USING LANDSAT-8 AND SENTINEL-2A SATELLITE

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Yamashiki, Y.^1¹  Yadav, S.^1²  Susaki, J.^2³  Yamashita, Y.^3⁴ 

[1] Department of Civil and Earth Resources Engineering, Graduate School of Engineering, Kyoto University, Kyoto 615-8540, Japan^2;Graduate School of Advanced Integrated Studies on Human Survivability, Kyoto University, Kyoto 606-8501, Japan^1;Kyoto University, Field Science Education and Research Center, Nagahama 625-0086, Japan^3;Lake Biwa Environmental Research Institute (LBERI), Otsu 520-0022, Japan^4

关键词: Chlorophyll-a;    Landsat-8;    Sentinel-2A;    Coastal Water;    Freshwater;    Satellite-Remote Sensing;   

DOI  :  10.5194/isprs-archives-XLII-3-W7-77-2019

学科分类：地球科学(综合)

来源: Copernicus Publications

【 摘 要 】

Chlorophyll-a is an optically active compound (OAC) commonly used as a proxy for phytoplankton biomass in an aquatic environment. Retrieving the concentration of chlorophyll-a remains a challenge due to the presence of several OAC particularly in water bodies which are in proximity to the land-based activities. In this study, an effort has been made to estimate the chlorophyll-a concentration of both the freshwater Lake Biwa and the coastal water of Wakasa Bay in Japan. A spectral decomposition algorithm was used to determine the chlorophyll-a using the satellite images. The algorithm was applied to the satellite images from two different sensors namely Landsat-8/OLI and Sentinel-2A/MSI. The satellite-derived chlorophyll-a concentration for the lake and coastal water from two different sensors were compared to assess the performance of both the sensors. The accuracy of the chlorophyll-a results derived from the images was evaluated with the in-situ measurement data of the chlorophyll-a for the Lake Biwa and the coastal water of Wakasa Bay. Both satellite sensors appear to give the best results for the coastal water (R² > 0.80) with an RMSE 2 > 0.70) than Landsat-8, with an RMSE of

【 授权许可】

CC BY